Senior Data Engineer (Snowflake)

Continuum Solutions; Houston (TX); On-site; USD 120,000 - 150,000; Full time

Job summary

A dynamic technology company in Texas is seeking a Senior Data Engineer to build and scale their data platform. You will design and optimize data pipelines utilizing Snowflake and cloud technologies such as AWS. Ideal candidates will have over 7 years of experience in data engineering and demonstrate expertise in delivering operational and analytical data solutions. This role offers opportunities to work on AI/ML initiatives and requires strong SQL and Python skills.

Qualifications

• 7+ years in data engineering roles with at least 3 years on cloud data platforms.
• Demonstrated expertise with Snowflake and at least one major cloud platform.
• Strong track record of delivering operational and analytical data pipelines.

Responsibilities

• Design, develop, and maintain data pipelines using Snowflake and AWS/Azure.
• Implement ETL/ELT processes to integrate data from diverse upstream systems.
• Lead the build and optimization of Snowflake-based data warehouses.

Skills

Snowflake

AWS

Data modeling

ETL/ELT

SQL

Python

CI/CD

Data governance

Agile methodology

Education

Bachelor’s degree in Computer Science, Engineering, or related field

Relevant certifications (SnowPro, AWS/Azure Data Engineer)

Tools

Azure Data Factory

Airflow

Power BI

Git

Job description

The Senior Data Engineer will play a critical role in building and scaling the company’s data platform to support analytics, reporting, and operational insights. This role requires deep expertise in Snowflake and cloud technologies (AWS), with strong upstream oil & gas domain knowledge. You’ll design and optimize data pipelines, enforce data quality and governance standards, and partner with business stakeholders to deliver reliable and scalable data solutions.

Key Responsibilities

• Design, develop, and maintain data pipelines using Snowflake, AWS/Azure, and modern data engineering tools.
• Implement ETL/ELT processes to integrate data from diverse upstream systems (SCADA, production accounting, drilling, completions, etc.).
• Architect and develop scalable data models that support both operational reporting and advanced analytics use cases.
• Establish frameworks for data quality, validation, and lineage to ensure trust in enterprise data.
• Lead the build and optimization of Snowflake-based data warehouses, focusing on performance and cost efficiency.
• Design and implement cloud-native data solutions leveraging AWS/Azure services (e.g., S3, Lambda, Azure Data Factory, Databricks).
• Manage large‑scale, time‑series, and operational data processing workflows.
• Implement robust security, access management, and governance practices.
• Provide technical guidance and mentor junior team members.
• Evaluate and introduce new technologies and best practices to enhance data platform capabilities.
• Build reusable components, frameworks, and automation utilities to accelerate delivery.
• Support AI/ML initiatives by delivering production‑ready, high‑quality data pipelines.
• Partner with stakeholders across business units to capture and translate data requirements into technical solutions.
• Collaborate with analysts and data scientists to enable self‑service analytics and business reporting.
• Deliver reliable data integration for regulatory and compliance reporting.
• Act as a bridge between technical teams and business leaders, ensuring alignment and impact.

Qualifications & Experience

Education

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related technical field.
• Advanced degree or relevant certifications (e.g., SnowPro, AWS/Azure Data Engineer, Databricks) preferred.

Experience

• 7+ years in data engineering roles with at least 3 years on cloud data platforms.
• Demonstrated expertise with Snowflake and at least one major cloud platform (AWS or Azure).
• Strong track record of delivering operational and analytical data pipelines.
• Advanced SQL Server and Python skills.
• Strong background in data modeling, ETL/ELT, cataloging, lineage, and security.
• Familiarity with orchestration tools (Airflow, Azure Data Factory, etc.).
• Proficiency with CI/CD pipelines, version control (Git), and automated testing practices.
• Experience with BI and visualization tools (Power BI, Spotfire, Tableau).
• Understanding of AI/ML concepts and preparing datasets for analytics.
• Familiarity with Agile methodology and Scrum framework; able to work in iterative sprints and adapt to changing priorities.
• Strong communication and stakeholder engagement skills, with the ability to influence both executives and technical peers.
• Knowledge of data governance, security standards, and regulatory compliance within the energy sector.

EEO Statement

This employer provides equal employment opportunities to all applicants and employees and prohibits discrimination on the basis of race, color, religion, sex (including pregnancy), gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other status protected by law. Reasonable accommodations are available upon request during the application process.